Systematic Mapping Study of Non-Functional Requirements in Big Data System

Context: The mobile app market is continually growing offering solutions to almost all aspects of people’s lives, e.g., healthcare, business, entertainment, as well as the stakeholders’ demand for apps that are more secure, portable, easy to use, among other non-functional requirements (NFRs). Therefore, manufacturers should guarantee that their mobile apps achieve high-quality levels. A good strategy is to include software testing and quality assurance activities during the whole life cycle of such solutions. Problem: Systematically warranting NFRs is not an easy task for any software product. Software engineers must take important decisions before adopting testing techniques and automation tools to support such endeavors. Proposal: To provide to the software engineers with a broad overview of existing dynamic techniques and automation tools for testing mobile apps regarding NFRs. Methods: We planned and conducted a Systematic Mapping Study (SMS) following well-established guidelines for executing secondary studies in software engineering. Results: We found 56 primary studies and characterized their contributions based on testing strategies, testing approaches, explored mobile platforms, and the proposed tools. Conclusions: The characterization allowed us to identify and discuss important trends and opportunities that can benefit both academics and practitioners.

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BIG HEALTH DATA: A SYSTEMATIC MAPPING STUDY

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w12-113-2019 ◽

2019 ◽

Vol XLII-4/W12 ◽

pp. 113-119

Author(s):

S. Lbrini ◽

A. Fadil ◽

H. Rhinane ◽

H. J. Oulidi

Keyword(s):

Remote Sensing ◽

Big Data ◽

Real Time ◽

Digital Libraries ◽

Research Area ◽

Health Data ◽

Systematic Mapping Study ◽

Data Systems ◽

Mapping Study ◽

Systematic Mapping

<p><strong>Abstract.</strong> The Big Data, a result of the digital revolution, offers several opportunities in the field of health. Indeed, appliances and applications permanently connected to humans and the global digitalization of medical documents produce a vast health data: "Big Health Data". This data is the subject of several projects in the world given the opportunities offered to optimize this area. This paper focuses on quantifying the production of scientific articles about Big Health Data research and the most investigated Big Health Data topics. It also presents a mapping of countries producing articles about this subject. In remote sensing using real time categories, we aimed to quantify articles dealing with “big data architectures”, technologies and data sources used. A systematic mapping study was conducted with a set of seven research questions by investigating articles from two digital libraries: Scopus and Springer. The study concern articles published in 2017 and the first half of 2018. The results are illustrated by diagrams answering each question from which a set of recommendations are concluded in this area of research. The study shows that this Data is used the most in studies of oncology. Statistics show that while remote sensing and monitoring is a hot topic, real-time use is not as interesting. It was found that there’s a lack in studies interested in big data technologies used in real time remote sensing in the field of health. In conclusion, we recommend more focus on research area treating architecture in remote sensing real time Big Health Data systems combined with geolocation.</p>

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